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Spatial Databases: With Application to GIS (The Morgan Kaufmann Series in Data Management Systems) 1st Edition

4.0 4.0 out of 5 stars 12 ratings

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Spatial Databases is the first unified, in-depth treatment of special techniques for dealing with spatial data, particularly in the field of geographic information systems (GIS). This book surveys various techniques, such as spatial data models, algorithms, and indexing methods, developed to address specific features of spatial data that are not adequately handled by mainstream DBMS technology.

The book also reviews commercial solutions to geographic data handling: ArcInfo, ArcView, and Smallworld GISs; and two extensions to the relational model, PostgreSQL and Oracle Spatial. The authors examine these underlying GIS technologies, assess their strengths and weaknesses, and consider specific uses for which each product is best suited.

* Examines the strengths of various query languages and approaches to query processing.* Explains the use of computational geometry in spatial databases GISs, providing necessary background and an in-depth look at key algorithms.* Covers spatial access methods, including the R-tree and several space-driven structures, and is filled with dozens of helpful illustrations.

Editorial Reviews

Review

"Spatial Databases covers all of the major themes of the field -- representation, query languages, computational geometry, spatial indexing -- using geographic information systems as the principal application domain and motivation. It is an excellent introduction for computer science professionals interested in exploring GIS, and an excellent resource for GIS professionals interested in learning more about the computer science foundations of the field." --Michael F. Goodchild, National Center for Geographic Information and Analysis, and University of California, Santa Barbara"Spatial Databases is a well-written, comprehensive treatment of a multi-disciplinary field, spanning computational geometry, database modeling, object-orientation, and query processing. The book presents both advanced research and commercial systems in a clear and accessible manner. This book is essential for understanding the current state of the art. Well done!" --Professor Dennis Shasha, New York University

From the Back Cover

"Spatial Databases covers all of the major themes of the field -- representation, query languages, computational geometry, spatial indexing -- using geographic information systems as the principal application domain and motivation. It is an excellent introduction for computer science professionals interested in exploring GIS, and an excellent resource for GIS professionals interested in learning more about the computer science foundations of the field."--Michael F. Goodchild, National Center for Geographic Information and Analysis, and University of California, Santa Barbara

"Spatial Databases is a well-written, comprehensive treatment of a multi-disciplinary field, spanning computational geometry, database modeling, object-orientation, and query processing. The book presents both advanced research and commercial systems in a clear and accessible manner. This book is essential for understanding the current state of the art. Well done!"--Professor Dennis Shasha, New York University

Spatial Databases is the first unified, in-depth treatment of special techniques for dealing with spatial data, particularly in the field of geographic information systems (GIS). This book surveys various techniques, such as spatial data models, algorithms, and indexing methods, developed to address specific features of spatial data that are not adequately handled by mainstream DBMS technology.

The book also reviews commercial solutions to geographic data handling: ArcInfo, ArcView, and Smallworld GISs; and two extensions to the relational model, PostgreSQL and Oracle Spatial. The authors examine these underlying GIS technologies, assess their strengths and weaknesses, and consider specific uses for which each product is best suited.

Features

  • Examines the strengths of various query languages and approaches to query processing.
  • Explains the use of computational geometry in spatial databases GISs, providing necessary background and an in-depth look at key algorithms.
  • Covers spatial access methods, including the R-tree and several space-driven structures, and is filled with dozens of helpful illustrations.

Product details

  • Publisher ‏ : ‎ Morgan Kaufmann; 1st edition (June 1, 2001)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 410 pages
  • ISBN-10 ‏ : ‎ 1558605886
  • ISBN-13 ‏ : ‎ 978-1558605886
  • Item Weight ‏ : ‎ 2.29 pounds
  • Dimensions ‏ : ‎ 7.67 x 1.18 x 9.58 inches
  • Customer Reviews:
    4.0 4.0 out of 5 stars 12 ratings

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Philippe Rigaux
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4 out of 5 stars
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Top reviews from the United States

  • Reviewed in the United States on October 18, 2002
    Very nicely written book. It is quite technical, with a very detailed and mathematically-oriented exposition. More suitable for a classroom teaching or for a GIS software developer/expert analyst than for the average user. Contains great chapters on representation of spatial objects and concepts, and computational geometry algorithms.
    A must have for a GIS software developer or a GIS analyst trying to gain a deeper understanding of GIS database organization and optimal query algorithms. Too deep for beginners and occasional GIS users.
    19 people found this helpful
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  • Reviewed in the United States on January 8, 2017
    One must reboot the Kindle app frequently because of two reasons: the page flipping gets buggy after a few minutes of reading (easily gets off center) and freezing of the entire app. This is a terrible experience for $80. Fit it.
  • Reviewed in the United States on December 29, 2008
    This textbook is an excellent resource for people specifically interested in the theoretical nuts and bolts of spatial databases. The book covers a lot of ground in just over 400 pages. It would be an excellent text for an advanced GIS programming course for either geography students or computer science students. For the geography student, the text provides an excellent coverage of database concepts while drawing on familiar topics. For the computer science student, the book extends basic knowledge of DBMS for spatial applications.

    The book is divided into eight chapters. Each chapter is completed with an excellent bibliographical review of relevant publications. This review, alone, is worth the price of the book.

    Chapter 1: Introduction to Spatial Database: Covers basic concepts of SQL, DBMS and spatial data.

    Chapter 2: Representation of Spatial Objects: This chapter should be familiar to anyone with a GIS background but would fill in the gaps for computer science students. The section on formats and standards is a bit dated but provides a nice theoretical background - especially for the Census TIGER data.

    Chapter 3: Logical Models and Query Languages: Opposite of Chapter 2, this chapter will challenge the Geography student while further grounding the Computer Science student in GIS data types.

    Chapter 4: The Constraint Data Model: Here the authors choose to introduce some unique material in the form of the constraint data model. The model is designed specifically to encode spatial data in a basic relational model. The chapter even breaks down the model into relational algebra statements. For most teaching purposes, this chapter can be skipped.

    Chapter 5: Computational Geometry: An odd gem in a text on spatial databases. This chapter provides a basic introduction to computation geometry techniques and their application to spatial data. One of the most significant aspects of a spatial databases is that it encodes geometric representations of geographic phenomena. Basic computational geometry is a necessary extension for a database to truly support spatial data. Pseudo-code is given but I would recommend the classic Computational Geometry in C (Cambridge Tracts in Theoretical Computer Science) for detailed implementations. This chapter will be challenging for Geography students but simple for Computer Science students.

    Chapter 6: Spatial Access Methods: The biggest challenge for spatial databases is spatial indexing - adding a true sense of "where" to SELECT...WHERE! The chapter focuses mostly on classical index structures - B-tree, R-Tree, etc. This would be a good chapter for a "short week" as it is either a research focus or matter of "it just works". Students who desire to research spatial indexing will find the chapter lacking. Others will find it overwhelming.

    Chapter 7: Query Processing: Like Chapter 6, this chapter delves into details that only a student truly interested in researching spatial indexes or developing new databases would be concerned with. The chapter presents how the spatial index is utilized for joins and relates.

    Chapter 8: Commercial Systems: Any book that attempts to survey existing software is always out of date. This chapter might be of historical interest but is hardly worth covering. The section of PostgreSQL is interesting but better material exists on the web.

    Overall, the book is well written and clearly presents the material. The coverage is focused on applications to spatial databases. My favorite advanced GIS textbook is GIS: A Computing Perspective, Second Edition.
    8 people found this helpful
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  • Reviewed in the United States on July 15, 2002
    I have been in GIS and graphics research and development for more than 10 years. GIS is a area that is mixed with technical and management issues greatly; therefore, there is very few truly technical books that is focus on computing issues in GIS.
    I am really excited to see this book because it compiles tons of research materials into 1 place. My 2 boxes full of research papers can go into basement while I am having this book as the constant reference. The book got a very coherent presentation of the large scale data management issues with GIS. Thier description is very accessible. They have tried their best to minimize the amount of mathematics that could be involved.
    If you are a beginner, this is a definite starting point to learn about various techniques and issues about spatial data management and computing. I wish I have this book at the start of my career. Much of my headaches to run through all of those research papers can be eliminated.
    If you want to implement a spatial data management system, this book alone is not enough. You may need to add few other graphics books and database books to acquire enough background to do so.
    Well, you can only ask for so much coverage for a single book.
    25 people found this helpful
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  • Reviewed in the United States on February 16, 2006
    Last summer, when I was asked to present an "Advanced GIS" course for some of grad students in Geomatics, I was fortunate enough to find this book on my first round of serach. It is a great book with deep technical explanation of the subject and its applications. It is more a type of textbook than a book can be used by general public. However, public users may still find some chapters informative. I recommend this book as a grad textbook for those who need technical undetrstanding of spatial databases in GIS.
    6 people found this helpful
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Top reviews from other countries

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  • Joao FirJur
    5.0 out of 5 stars Excellent Book
    Reviewed in Brazil on August 20, 2020
    Perfect!
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    Joao FirJur
    5.0 out of 5 stars
    Excellent Book

    Reviewed in Brazil on August 20, 2020
    Perfect!
    Images in this review
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  • cp
    4.0 out of 5 stars trés bon livre trés synthétique
    Reviewed in France on April 18, 2014
    un livre trés synthétique permettant d'appréhender en détail pas mal de notions : il aurait été parfait si quelques exemples en C avaient été joints afin d'assimiler les concepts et les algorithmes et pouvoir les tester rapidement.
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